Flow control of input/output (io) in a synchronous replication session

ABSTRACT

An aspect of performing flow control of IO in a synchronous replication session between a local storage and a remote storage of a storage system includes tracking an amount of time an input/output (IO) request is processed at the remote storage including an amount of time the IO request is in transmit to and from the remote storage system. The amount of time indicates a remote latency value. An aspect also includes tracking an amount of time the IO request is processed at the local storage and calculating a difference between the remote latency value and the amount of time the IO request is processed at the local storage. The difference indicates a local latency value. An aspect further includes modifying an amount of IO requests admitted at the storage system as a function of the local latency value.

BACKGROUND

Many information processing systems are configured to replicate datafrom one storage system to another storage system, possibly at differentphysical sites. In some cases, such arrangements are utilized to supportdisaster recovery functionality within the information processingsystem. For example, an enterprise may replicate data from a productiondata center to a disaster recovery data center. In the event of adisaster at the production site, applications can be started at thedisaster recovery site using the data that has been replicated to thatsite so that the enterprise can continue its business.

Data replication in these and other contexts can be implemented usingasynchronous replication at certain times and synchronous replication atother times. For example, asynchronous replication may be configured toperiodically transfer data in multiple cycles from a local site to aremote site, while synchronous replication may be configured to mirrorhost writes from the local site to the remote site as the writes aremade at the local site. Storage systems participating in a replicationprocess can therefore each be configured to support both asynchronousand synchronous replication modes.

Storage systems are designed to handle various levels of IO workload.When the workload is well within the designed load capacity, IOprocessing latency is typically flat. When the workload approaches orexceeds a designed capacity, processing latency may increase sharply.After workload exceeds a certain tipping point, the system may be pushedout of a stable state, and the IO handling latency may growexponentially. Thus, it is advantageous for a system to control theworkload within the tipping point and prevent overload from happening.On the other hand, it is disadvantageous for a system to control theworkload too aggressively, as it may cause the system to beunderutilized.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described herein in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

One aspect provides a method for flow control in a synchronousreplication session between a local storage and a remote storage of astorage system. The method includes tracking an amount of time aninput/output (IO) request is processed at the remote storage includingan amount of time the IO request is in transmit to and from the remotestorage system. The amount of time indicates a remote latency value. Themethod also includes tracking an amount of time the IO request isprocessed at the local storage and calculating a difference between theremote latency value and the amount of time the IO request is processedat the local storage. The difference indicates a local latency value.The method further includes modifying an amount of IO requests admittedat the storage system as a function of the local latency value.

Another aspect provides a system for flow control in a synchronousreplication session between a local storage and a remote storage of astorage system. The system includes a memory having computer-executableinstructions and a processor operable by a storage system. The processorexecutes the computer-executable instructions. The computer-executableinstructions when executed by the processor cause the processor toperform operations. The operations include tracking an amount of time aninput/output (IO) request is processed at the remote storage includingan amount of time the IO request is in transmit to and from the remotestorage system. The amount of time indicates a remote latency value. Theoperations also include tracking an amount of time the IO request isprocessed at the local storage and calculating a difference between theremote latency value and the amount of time the IO request is processedat the local storage. The difference indicates a local latency value.The operations further include modifying an amount of IO requestsadmitted at the storage system as a function of the local latency value.

A further aspect provides a computer program product for flow control ina synchronous replication session between a local storage and a remotestorage of a storage system. The computer program product includes thecomputer program product embodied on a non-transitory computer readablemedium, the computer program product including instructions that, whenexecuted by a computer, cause the computer to perform operations. Theoperations include tracking an amount of time an input/output (IO)request is processed at the remote storage including an amount of timethe IO request is in transmit to and from the remote storage system. Theamount of time indicates a remote latency value. The operations alsoinclude tracking an amount of time the IO request is processed at thelocal storage and calculating a difference between the remote latencyvalue and the amount of time the IO request is processed at the localstorage. The difference indicates a local latency value. The operationsfurther include modifying an amount of IO requests admitted at thestorage system as a function of the local latency value.

BRIEF DESCRIPTION OF THE DRAWINGS

Objects, aspects, features, and advantages of embodiments disclosedherein will become more fully apparent from the following detaileddescription, the appended claims, and the accompanying drawings in whichlike reference numerals identify similar or identical elements.Reference numerals that are introduced in the specification inassociation with a drawing figure may be repeated in one or moresubsequent figures without additional description in the specificationin order to provide context for other features. For clarity, not everyelement may be labeled in every figure. The drawings are not necessarilyto scale, emphasis instead being placed upon illustrating embodiments,principles, and concepts. The drawings are not meant to limit the scopeof the claims included herewith.

FIG. 1 depicts a block diagram of an information processing systemincluding local and remote storage systems configured with functionalityfor implementing IO flow control in a synchronous replication sessionaccording to an embodiment;

FIG. 2 is a flow diagram of a process for implementing IO flow controlin a synchronous replication session according to an embodiment;

FIG. 3 is a diagram depicting a time-based sequence of the IO flowcontrol process of FIG. 2 according to an embodiment;

FIG. 4 depicts a content addressable storage system having a distributedstorage controller configured with functionality for implementing IOflow control in a synchronous replication session according to anembodiment;

FIG. 5 depicts a cloud infrastructure-based processing platform withphysical and virtual processing resources for implementing IO flowcontrol in a synchronous replication session in accordance with anembodiment; and

FIG. 6 depicts an alternative processing platform for implementing IOflow control in a synchronous replication session in accordance with anembodiment.

DETAILED DESCRIPTION

As an initiator's IO load increases so does its internal storage arraylatency to handle the IO. At some point, further increases of the loadcan lead to internal resource contention and even higher latency growthwhile decreasing IO bandwidth. Some storage systems have flow controlmechanisms to target an optimal array performance and preventuncontrolled latency growth. Such flow control methods may monitor thenumber of incoming IO and their internal average latency to estimateinternal resource utilization. When the internal latency grows abovesystem-defined limits, the flow control may start throttling incoming IOto prevent system overload. The embodiments described herein can be usedin conjunction with a flow control system and method described incommonly assigned U.S. patent Ser. No. 10/048,874 (hereinafter '874),entitled “Flow Control With a Dynamic Window in a Storage System WithLatency Guarantees,” which utilizes a dynamic window size that isadjusted based on averaged end-to-end latency of IO operations. Theembodiments may also be used in conjunction with a flow control systemand method described in commonly assigned U.S. patent application Ser.No. 16/047,087 (hereinafter '087), entitled “Method and Apparatus forDynamic Flow Control in Distributed Storage Systems,” which furtherextends dynamic flow control for IO in distributed storage systems. Boththe '874 patent and the '087 application are incorporated by referenceherein in their entireties.

If synchronous (sync) replication is configured for a storage array, IOis acknowledged to the initiator only after it is completed on both thelocal and remote arrays. Thus, IO latency when performing a write tosync replication volume is naturally larger than the latency of a localIO operation. This presents challenges for the above-described aboveflow control algorithm as it may identify high internal IO latency andincorrectly decide that the system is overloaded. In addition, adding tothe remote latency operation, the round trip time (RTT), which is thetime it takes for an operation to transmit back and forth between thelocal storage and the remote storage, can also add to the overall IOlatency. If a flow control monitors IO latency from the time it entersthe storage array until IO handling is completed, the link RTT andremote write latency are included into the IO latency measure. This mayresult in flow control detecting high latency in the presence of syncreplication operations and concluding that the local array isoverloaded.

Illustrative embodiments provide a storage system with functionality forflow control of IO during a synchronous replication session. Theembodiments provide a solution to handle high sync replication latencywhile maintaining optimal flow control. The processes described hereinprovide the ability to manage high sync replication delays withoutthrottling local IO operations and impacting overall array performance.The illustrative embodiments describe a process that is based on thenotion that additional latency introduced by mirroring data to a remotesystem does not reflect or represent IO load and resource utilization ona local cluster. Thus, it should not affect the flow control decision tothrottle incoming IO. By removing this additional latency from themonitored data, the processes can take into consideration only locallatency. This will allow a cluster to handle more incoming IO requestsas long as the local latency is within the system's defined limits,which can improve overall storage array performance.

FIG. 1 shows an information processing system 100 configured inaccordance with an illustrative embodiment. The information processingsystem 100 comprises a plurality of host devices 101, a local storagesystem 102L (also referred to herein as “source” storage system) and aremote storage system 102R (also referred to herein as “target” storagesystem). The local storage system and the remote storage system arecollectively referred to herein as storage systems 102. The host devices101 and storage systems 102 are each configured to communicate with oneanother over a network 104. The local and remote storage systems 102 aremore particularly configured in this embodiment to participate in asynchronous replication process in which one or more storage volumes aresynchronously replicated from the local storage system 102L to theremote storage system 102R, possibly with involvement of at least one ofthe host devices 101. The one or more storage volumes that aresynchronously replicated from the local storage system 102L to theremote storage system 102R are illustratively part of a designatedconsistency group.

Each of the storage systems 102 is illustratively associated with acorresponding set of one or more of the host devices 101. The hostdevices 101 illustratively comprise servers or other types of computersof an enterprise computer system, cloud-based computer system or otherarrangement of multiple compute nodes associated with respective users.

The host devices 101 in some embodiments illustratively provide computeservices such as execution of one or more applications on behalf of eachof one or more users associated with respective ones of the hostdevices. Such applications illustratively generate input/output (IO)operations that are processed by a corresponding one of the storagesystems 102. The term “IO” as used herein refers to at least one ofinput and output. For example, IO operations may comprise write requestsand/or read requests directed to stored data of a given one of thestorage systems 102. The storage systems 102 illustratively compriserespective processing devices of one or more processing platforms. Forexample, the storage systems 102 can each comprise one or moreprocessing devices each having a processor and a memory, possiblyimplementing virtual machines and/or containers, although numerous otherconfigurations are possible.

The storage systems 102 may be implemented on a common processingplatform, or on separate processing platforms.

The host devices 101 are illustratively configured to write data to andread data from the storage systems 102 in accordance with applicationsexecuting on those host devices for system users.

The term “user” herein is intended to be broadly construed so as toencompass numerous arrangements of human, hardware, software or firmwareentities, as well as combinations of such entities. Compute and/orstorage services may be provided for users under a Platform-as-a-Service(PaaS) model, an Infrastructure-as-a-Service (IaaS) model and/or aFunction-as-a-Service (FaaS) model, although it is to be appreciatedthat numerous other cloud infrastructure arrangements could be used.Also, illustrative embodiments can be implemented outside of the cloudinfrastructure context, as in the case of a stand-alone computing andstorage system implemented within a given enterprise.

The network 104 is assumed to comprise a portion of a global computernetwork such as the Internet, although other types of networks can bepart of the network 104, including a wide area network (WAN), a localarea network (LAN), a satellite network, a telephone or cable network, acellular network, a wireless network such as a WiFi or WiMAX network, orvarious portions or combinations of these and other types of networks.The network 104 in some embodiments therefore comprises combinations ofmultiple different types of networks each comprising processing devicesconfigured to communicate using Internet Protocol (IP) or othercommunication protocols.

As a more particular example, some embodiments may utilize one or morehigh-speed local networks in which associated processing devicescommunicate with one another utilizing Peripheral Component Interconnectexpress (PCIe) cards of those devices, and networking protocols such asInfiniBand, Gigabit Ethernet or Fibre Channel. Numerous alternativenetworking arrangements are possible in a given embodiment, as will beappreciated by those skilled in the art.

The local storage system 102L comprises a plurality of storage devices106L and an associated storage controller 108L. The storage devices 106Lstore storage volumes 110L and queues 115L. The storage volumes 110Lillustratively comprise respective logical units (LUNs) or other typesof logical storage volumes. The queues 115L may store incoming IOswaiting to be processed by the local storage system 102L.

Similarly, the remote storage system 102R comprises a plurality ofstorage devices 106R and an associated storage controller 108R. Thestorage devices 106R store storage volumes 110R, at least a portion ofwhich represent respective LUNs or other types of logical storagevolumes that are replicated from the local storage system 102L to theremote storage system 102R in accordance with a synchronous replicationprocess. The storage devices 106R also store one or more queues 115R.

The storage devices 106 of the storage systems 102 illustrativelycomprise solid state drives (SSDs). Such SSDs are implemented usingnon-volatile memory (NVM) devices such as flash memory. Other types ofNVM devices that can be used to implement at least a portion of thestorage devices 106 include non-volatile random access memory (NVRAM),phase-change RAM PC-RAM) and magnetic RAM (MRAM). These and variouscombinations of multiple different types of NVM devices may also beused. For example, hard disk drives (HDDs) can be used in combinationwith or in place of SSDs or other types of NVM devices.

However, it is to be appreciated that other types of storage devices canbe used in other embodiments. For example, a given storage system as theterm is broadly used herein can include a combination of different typesof storage devices, as in the case of a multi-tier storage systemcomprising a flash-based fast tier and a disk-based capacity tier. Insuch an embodiment, each of the fast tier and the capacity tier of themulti-tier storage system comprises a plurality of storage devices withdifferent types of storage devices being used in different ones of thestorage tiers.

For example, the fast tier may comprise flash drives or other types ofSSDs while the capacity tier comprises HDDs. The particular storagedevices used in a given storage tier may be varied in other embodiments,and multiple distinct storage device types may be used within a singlestorage tier. The term “storage device” as used herein is intended to bebroadly construed, to encompass, for example, SSDs, HDDs, flash drives,hybrid drives or other types of storage devices.

In some embodiments, at least one of the storage systems 102illustratively comprises a scale-out all-flash content addressablestorage array such as an XtremIO storage array, of DELL EMC ofHopkinton, Mass.

The term “storage system” as used herein is therefore intended to bebroadly construed and should not be viewed as being limited to contentaddressable storage systems or flash-based storage systems. A givenstorage system as the term is broadly used herein can comprise, forexample, network-attached storage (NAS), storage area networks (SANs),direct-attached storage (DAS) and distributed DAS, as well ascombinations of these and other storage types, includingsoftware-defined storage.

The storage controller 108L of local storage system 102L in the FIG. 1embodiment includes replication control logic 112L and a flow controller114L.

Similarly, the storage controller 108R of remote storage system 102Rincludes replication control logic 112R and a flow controller 114T.

Although not explicitly shown in the Figure, additional components canbe included in the storage controllers 108, such as signature generatorsutilized in generating content-based signatures of data pages.

The instances of replication control logic 112L and 112R arecollectively referred to herein as replication control logic 112. Suchreplication control logic instances are also referred to herein asindividually or collectively comprising at least a portion of a“replication engine” of the system 100.

The replication control logic 112 of the storage systems 102 controlsperformance of the synchronous replication process carried out betweenthose storage systems, which as noted above in some embodiments furtherinvolves at least one of the host devices 101. The data replicated fromthe local storage system 102L to the remote storage system 102R caninclude all of the data stored in the local storage system 102L, or onlycertain designated subsets of the data stored in the local storagesystem 102L, such as particular designated sets of LUNs or other logicalstorage volumes. Different replication processes of different types canbe implemented for different parts of the stored data. Also, the storagesystems 102 can be configured to operate in different replication modesof different types at different times.

A given storage volume designated for replication from the local storagesystem 102L to the remote storage system 102R illustratively comprises aset of one or more LUNs or other instances of the storage volumes 110Lof the local storage system 102L. Each such LUN or other storage volumeillustratively comprises at least a portion of a physical storage spaceof one or more of the storage devices 106L. The corresponding replicatedLUN or other storage volume of the storage volumes 110R of the remotestorage system 102R illustratively comprises at least a portion of aphysical storage space of one or more of the storage devices 106R.

The replication control logic 112 of the storage systems 102 in someembodiments is configured to control the performance of correspondingportions of a synchronous replication process of the type illustrated inthe flow diagram of FIG. 2.

The storage controllers 108 of the storage systems 102 should also beunderstood to include additional modules and other components typicallyfound in conventional implementations of storage controllers and storagesystems, although such additional modules and other components areomitted from the figure for clarity and simplicity of illustration.

It will be assumed for the following description of the FIG. 1embodiment that there is an ongoing synchronous replication processbeing carried out between the local storage system 102L and the remotestorage system 102R in the system 100, utilizing their respectiveinstances of replication control logic 112L and 112R.

The synchronous replication process more particularly comprises asynchronous replication process in which a consistency group comprisingone or more storage volumes is replicated from the local storage system102L to the remote storage system 102R as part of host IO handling. Suchan arrangement is illustratively configured to guarantee dataconsistency between the storage volumes of the consistency group on thelocal and their corresponding replicated versions on the remote. Thesynchronous replication is illustratively implemented at least in partby or otherwise under the control of the local and remote instances ofreplication control logic 112L and 112R. Other types of replicationarrangements can be used in other embodiments.

In embodiments in which the storage systems 102 comprise contentaddressable storage systems, address metadata is illustratively utilizedto provide content addressable storage functionality within thosesystems. The address metadata in some embodiments comprises at least aportion of one or more logical layer mapping tables that map logicaladdresses of respective ones of the data pages of the storage volume tocorresponding content-based signatures of the respective data pages.Examples of logical layer mapping tables and other metadata structuresmaintained by at least the storage controller 108R of remote storagesystem 102R will be described elsewhere herein.

The storage systems 102 in the FIG. 1 embodiment are assumed to beimplemented using at least one processing platform each comprising oneor more processing devices each having a processor coupled to a memory.Such processing devices can illustratively include particulararrangements of compute, storage and network resources.

The storage systems 102 may be implemented on respective distinctprocessing platforms, although numerous other arrangements are possible.At least portions of their associated host devices may be implemented onthe same processing platforms as the storage systems 102 or on separateprocessing platforms.

The term “processing platform” as used herein is intended to be broadlyconstrued so as to encompass, by way of illustration and withoutlimitation, multiple sets of processing devices and associated storagesystems that are configured to communicate over one or more networks.For example, distributed implementations of the system 100 are possible,in which certain components of the system reside in one data center in afirst geographic location while other components of the system reside inone or more other data centers in one or more other geographic locationsthat are potentially remote from the first geographic location. Thus, itis possible in some implementations of the system 100 for the storagesystems 102 to reside in different data centers. Numerous otherdistributed implementations of the storage systems 102 and theirrespective associated sets of host devices are possible.

Additional examples of processing platforms utilized to implementstorage systems and possibly their associated host devices inillustrative embodiments will be described in more detail below inconjunction with FIGS. 5 and 6.

It is to be appreciated that these and other features of illustrativeembodiments are presented by way of example only and should not beconstrued as limiting in any way.

Accordingly, different numbers, types and arrangements of systemcomponents such as host devices 101, storage systems 102, network 104,storage devices 106, storage controllers 108 and storage volumes 110 canbe used in other embodiments.

It should be understood that the particular sets of modules and othercomponents implemented in the system 100 as illustrated in FIG. 1 arepresented by way of example only. In other embodiments, only subsets ofthese components, or additional or alternative sets of components, maybe used, and such components may exhibit alternative functionality andconfigurations.

For example, in other embodiments, at least portions of theabove-described functionality for flow control in a synchronousreplication process can be implemented in one or more host devices, orpartially in a host device and partially in a storage system.Illustrative embodiments are not limited to arrangements in which allsuch functionality is implemented in local and remote storage systems ora host device, and therefore encompass various hybrid arrangements inwhich the functionality is distributed over one or more storage systemsand one or more associated host devices, each comprising one or moreprocessing devices. References herein to “one or more processingdevices” configured to implement particular operations or otherfunctionality should be understood to encompass a wide variety ofdifferent arrangements involving one or more processing devices of atleast one storage system and/or at least one host device.

As another example, it is possible in some embodiments that the localstorage system and the remote storage system can comprise differentportions of the same storage system. In such an arrangement, areplication process is illustratively implemented to replicate data fromone portion of the storage system to another portion of the storagesystem. The terms “local storage system” and “remote storage system” asused herein are therefore intended to be broadly construed so as toencompass such possibilities.

The operation of the information processing system 100 will now bedescribed in further detail with reference to the flow diagram of theillustrative embodiment of FIG. 2, which implements a synchronousreplication process. The steps of the process illustratively involveinteractions between a local storage system and a remote storage system,referred to as respective “local” and “remote” in these Figures,illustratively utilizing replication control logic instances and flowcontrollers of storage controllers of the local and remote. For example,replication control logic of the local interacts with replicationcontrol logic of the remote in performing multiple cycles of synchronousreplication for a consistency group. It is possible in other embodimentsthat at least one of the storage systems does not include replicationcontrol logic and a flow controller, and in such embodiments thesecomponents are instead implemented in one or more host devices.

The synchronous replication process as illustrated in FIG. 2 is suitablefor use in system 100 but is more generally applicable to other types ofinformation processing systems in which data is replicated from local toremote. Also, the roles of local and remote can be reversed, as in asituation in which a failover from local to remote occurs.

In block 202, the process 200 tracks an amount of time an input/output(IO) request is processed at the remote storage including an amount oftime the IO request is in transmit to and from the remote storagesystem. The amount of time indicates a remote latency value.

In block 204, the process 200 tracks an amount of time the IO request isprocessed at the local storage. This amount of time includes both localprocessing time and remote processing time.

In block 206, the process 200 calculates a difference between the remotelatency value and the amount of time the IO request is processed at thelocal storage. The difference indicates a local latency value.

In block 208, the process 200 modifies an amount of IO requests admittedat the storage system as a function of the local latency value. Forexample, if the local latency value is less than a threshold value(indicating that the latency is low at the local storage), the process200 increases the amount of IO admitted to the system (block 210). If,on the other hand, if the local latency value exceeds the thresholdvalue (indicating that the latency is high at the local storage), theprocess 200 decreases the amount of IO admitted to the system (block212). Likewise, if the local latency value meets the threshold value,the process 200 maintains the current amount of IO admitted to thesystem (block 214).

Turning now to FIG. 3 a diagram 300 depicting a time sequence of theflow control process 200 described in FIG. 2 will now be described.

In FIG. 3, a local storage 302 and a remote storage 304 is shown. Thelocal storage may correspond to the local storage system 102L in FIG. 1and the remote storage 304 may correspond to the remote storage system102R in FIG. 1.

As shown in FIG. 3, an IO request is received at the local storage 302(e.g., from host 101 of FIG. 1). The local storage 302 records atimestamp 310 of the time the IO request is received at the localstorage. The local storage, as part of the synchronous replicationsession, mirrors the IO request to the remote storage 304 and records atimestamp 312 of the time the mirroring is initiated.

Simultaneous with the mirroring step, the local storage beginsprocessing the IO request at the local storage. The IO processed at thelocal storage is referred to as a local IO. Likewise, the remote storagereceives the mirrored IO request and begins processing/replication ofthe mirrored IO request at the remote storage. Upon completion of theprocessing of the mirrored IO at the remote storage, the remote storage,as part of the synchronous replication process, sends an acknowledgementto the local storage indicating successful completion of the processing.

The local storage, upon receiving this acknowledgement, records atimestamp that the acknowledgement was received 314. The duration oftime that elapses between timestamps 312 and 314 indicate processingtime attributed to the remote storage activities, as well as linktransmissions to and from the local and remote systems. This duration oftime is referred to as remote latency 320.

The local storage processes the local IO request and records a timestampwhen the processing of the local IO has completed 316. The local storagemay then calculate the duration of the local IO processing bycalculating the difference between the timestamp at 310 and thetimestamp at 316 (i.e., the time duration between when the IO wasinitially received at the local storage and when the IO completedprocessing at the local storage.

The local storage calculates a difference between the timestamp at 316and the remote latency value (the time it took to process theremote/mirrored IO at the remote storage including transit time) toidentify the actual latency value attributed to the processing of the IOat the local storage.

Determining this local latency value can then be used to modify, ifneeded, the amount of IO admitted to the system, as described in FIG. 2.

The particular processing operations and other system functionalitydescribed in conjunction with the flow diagram of FIG. 2 and diagram 300of FIG. 3 are presented by way of illustrative example only and shouldnot be construed as limiting the scope of the disclosure in any way.Alternative embodiments can use other types of processing operations toprovide flow control in conjunction with a synchronous replicationprocess. For example, the ordering of the process steps may be varied inother embodiments, or certain steps may be performed at least in partconcurrently with one another rather than serially. Also, one or more ofthe process steps may be repeated periodically, or multiple instances ofthe process can be performed in parallel with one another in order toimplement a plurality of different synchronous replication processes forrespective different consistency groups comprising different sets ofstorage volumes or for different storage systems or portions thereofwithin a given information processing system.

Functionality such as that described in conjunction with the flowdiagram of FIG. 2 can be implemented at least in part in the form of oneor more software programs stored in memory and executed by a processorof a processing device such as a computer or server. As will bedescribed below, a memory or other storage device having executableprogram code of one or more software programs embodied therein is anexample of what is more generally referred to herein as a“processor-readable storage medium.”

For example, storage controllers such as storage controllers 108 ofstorage systems 102 that are configured to control performance of one ormore steps of the FIG. 2 process in their corresponding system 100 canbe implemented as part of what is more generally referred to herein as aprocessing platform comprising one or more processing devices eachcomprising a processor coupled to a memory. A given such processingdevice may correspond to one or more virtual machines or other types ofvirtualization infrastructure such as Docker containers or Linuxcontainers (LXCs). The storage controllers 108, as well as other systemcomponents, may be implemented at least in part using processing devicesof such processing platforms. For example, in a distributedimplementation of a given one of the storage controllers 108, respectivedistributed modules of such a storage controller can be implemented inrespective containers running on respective ones of the processingdevices of a processing platform.

In some implementations of the FIG. 2 process, the local and remotestorage systems comprise content addressable storage systems configuredto maintain various metadata structures that are utilized in the flowcontrol processes. Examples of metadata structures maintained by thelocal and remote storage systems in illustrative embodiments include thelogical layer and physical layer mapping tables described below. It isto be appreciated that these particular tables are only examples, andother tables or metadata structures having different configurations ofentries and fields can be used in other embodiments.

An address-to-hash (“A2H”) utilized in some embodiments comprises aplurality of entries accessible utilizing logical addresses asrespective keys, with each such entry of the A2H table comprising acorresponding one of the logical addresses, a corresponding hash handle,and possibly one or more additional fields.

A hash-to-data (“H2D”) table utilized in some embodiments comprises aplurality of entries accessible utilizing hash handles as respectivekeys, with each such entry of the H2D table comprising a correspondingone of the hash handles, a physical offset of a corresponding one of thedata pages, and possibly one or more additional fields.

A hash metadata (“HMD”) table utilized in some embodiments comprises aplurality of entries accessible utilizing hash handles as respectivekeys. Each such entry of the HMD table comprises a corresponding one ofthe hash handles, a corresponding reference count and a correspondingphysical offset of one of the data pages. A given one of the referencecounts denotes the number of logical pages in the storage system thathave the same content as the corresponding data page and therefore pointto that same data page via their common hash digest. The HMD table mayalso include one or more additional fields.

A physical layer based (“PLB”) table utilized in some embodimentsillustratively comprises a plurality of entries accessible utilizingphysical offsets as respective keys, with each such entry of the PLBtable comprising a corresponding one of the physical offsets, acorresponding one of the hash digests, and possibly one or moreadditional fields.

As indicated above, the hash handles are generally shorter in lengththan the corresponding hash digests of the respective data pages, andeach illustratively provides a short representation of the correspondingfull hash digest. For example, in some embodiments, the full hashdigests are 20 bytes in length, and their respective corresponding hashhandles are illustratively only 4 or 6 bytes in length.

Also, it is to be appreciated that terms such as “table” and “entry” asused herein are intended to be broadly construed, and the particularexample table and entry arrangements described above can be varied inother embodiments. For example, additional or alternative arrangementsof entries can be used.

In some embodiments, the storage system may comprise an XtremIO storagearray or other type of content addressable storage system suitablymodified to incorporate functionality for flow control processes inconjunction with a synchronous replication process as disclosed herein.

An illustrative embodiment of such a content addressable storage systemwill now be described with reference to FIG. 4. In this embodiment, acontent addressable storage system 405 comprises a plurality of storagedevices 406 and an associated storage controller 408. The contentaddressable storage system 405 may be viewed as a particularimplementation of a given one of the storage systems 102, andaccordingly is assumed to be coupled to the other one of the storagesystems 102 and to one or more host devices of a computer system withininformation processing system 100.

Although it is assumed that both the local storage system 102L and theremote storage system 102R are content addressable storage systems insome embodiments, other types of storage systems can be used for one orboth of the local storage system 102L and the remote storage system 102Rin other embodiments. For example, it is possible that at least one ofthe storage systems 102 in an illustrative embodiment need not be acontent addressable storage system and need not include an ability togenerate content-based signatures. In such an embodiment, at leastportions of the process functionality of the one or more storage systemscan be implemented in a host device.

The storage controller 408 in the present embodiment is configured toimplement functionality for flow control processes of the typepreviously described in conjunction with FIGS. 1 through 3. For example,the content addressable storage system 405 illustratively participatesas a local storage system in a synchronous replication process with aremote storage system that may be implemented as another instance of thecontent addressable storage system 405.

The storage controller 408 includes distributed modules 412 and 414,which are configured to operate in a manner similar to that describedabove for respective corresponding replication control logic 112 andflow controllers 114 of the storage controllers 108 of system 100.Module 412 is more particularly referred to as distributed replicationcontrol logic, and illustratively comprises multiple replication controllogic instances on respective ones of a plurality of distinct nodes.Module 414 is more particularly referred to as a distributed flowcontroller, and illustratively comprises multiple flow control instanceson respective ones of the distinct nodes.

The content addressable storage system 405 in the FIG. 4 embodiment isimplemented as at least a portion of a clustered storage system andincludes a plurality of storage nodes 415 each comprising acorresponding subset of the storage devices 406. Such storage nodes 415are examples of the “distinct nodes” referred to above, and otherclustered storage system arrangements comprising multiple storage nodesand possibly additional or alternative nodes can be used in otherembodiments. A given clustered storage system may therefore include notonly storage nodes 415 but also additional storage nodes, compute nodesor other types of nodes coupled to network 104. Alternatively, suchadditional storage nodes may be part of another clustered storage systemof the system 100. Each of the storage nodes 415 of the storage system405 is assumed to be implemented using at least one processing devicecomprising a processor coupled to a memory.

The storage controller 408 of the content addressable storage system 405is implemented in a distributed manner so as to comprise a plurality ofdistributed storage controller components implemented on respective onesof the storage nodes 415. The storage controller 408 is therefore anexample of what is more generally referred to herein as a “distributedstorage controller.” In subsequent description herein, the storagecontroller 408 is referred to as distributed storage controller 408.

Each of the storage nodes 415 in this embodiment further comprises a setof processing modules configured to communicate over one or morenetworks with corresponding sets of processing modules on other ones ofthe storage nodes 415. The sets of processing modules of the storagenodes 415 collectively comprise at least a portion of the distributedstorage controller 408 of the content addressable storage system 405.

The modules of the distributed storage controller 408 in the presentembodiment more particularly comprise different sets of processingmodules implemented on each of the storage nodes 415. The set ofprocessing modules of each of the storage nodes 415 comprises at least acontrol module 408C, a data module 408D and a routing module 408R. Thedistributed storage controller 408 further comprises one or moremanagement (“MGMT”) modules 408M. For example, only a single one of thestorage nodes 415 may include a management module 408M. It is alsopossible that management modules 408M may be implemented on each of atleast a subset of the storage nodes 415. A given set of processingmodules implemented on a particular one of the storage nodes 415therefore illustratively includes at least one control module 408C, atleast one data module 408D and at least one routing module 408R, andpossibly a management module 408M.

Communication links may be established between the various processingmodules of the distributed storage controller 408 using well-knowncommunication protocols such as IP, Transmission Control Protocol (TCP),and remote direct memory access (RDMA). For example, respective sets ofIP links used in data transfer and corresponding messaging could beassociated with respective different ones of the routing modules 408R.

Although shown as separate modules of the distributed storage controller408, the modules 412 and 414 in the present embodiment are assumed to bedistributed at least in part over at least a subset of the other modules408C, 408D, 408R and 408M of the storage controller 408. Accordingly, atleast portions of the flow control functionality of the modules 412 and414 may be implemented in one or more of the other modules of thestorage controller 408. In other embodiments, the modules 412 and 414may be implemented as stand-alone modules of the storage controller 408.

The storage devices 406 may be configured to store volumes 418, metadatapages 420, and user data pages 422 and may also store additionalinformation not explicitly shown such as checkpoints and write journals.The metadata pages 420 and the user data pages 422 are illustrativelystored in respective designated metadata and user data areas of thestorage devices 406. Accordingly, metadata pages 420 and user data pages422 may be viewed as corresponding to respective designated metadata anduser data areas of the storage devices 406. A given “page” as the termis broadly used herein should not be viewed as being limited to anyparticular range of fixed sizes. In some embodiments, a page size of 8kilobytes (KB) is used, but this is by way of example only and can bevaried in other embodiments. For example, page sizes of 4 KB, 16 KB orother values can be used. Accordingly, illustrative embodiments canutilize any of a wide variety of alternative paging arrangements fororganizing the metadata pages 420 and the user data pages 422.

The user data pages 422 are part of a plurality of LUNs configured tostore files, blocks, objects or other arrangements of data, each alsogenerally referred to herein as a “data item,” on behalf of users of thecontent addressable storage system 405. Each such LUN may compriseparticular ones of the above-noted pages of the user data area. The userdata stored in the user data pages 422 can include any type of user datathat may be utilized in the system 100. The term “user data” herein istherefore also intended to be broadly construed.

A given storage volume for which content-based signatures are generatedusing modules 412 and 414 illustratively comprises a set of one or moreLUNs, each including multiple ones of the user data pages 422 stored instorage devices 406. The content addressable storage system 405 in theembodiment of FIG. 4 is configured to generate hash metadata providing amapping between content-based digests of respective ones of the userdata pages 422 and corresponding physical locations of those pages inthe user data area. Content-based digests generated using hash functionsare also referred to herein as “hash digests.” Such hash digests orother types of content-based digests are examples of what are moregenerally referred to herein as “content-based signatures” of therespective user data pages 422. The hash metadata generated by thecontent addressable storage system 405 is illustratively stored asmetadata pages 420 in the metadata area. The generation and storage ofthe hash metadata is assumed to be performed under the control of thestorage controller 408.

Each of the metadata pages 420 characterizes a plurality of the userdata pages 422. For example, a given set of user data pages representinga portion of the user data pages 422 illustratively comprises aplurality of user data pages denoted User Data Page 1, User Data Page 2,. . . User Data Page n. Each of the user data pages in this example ischaracterized by a LUN identifier, an offset and a content-basedsignature. The content-based signature is generated as a hash functionof content of the corresponding user data page. Illustrative hashfunctions that may be used to generate the content-based signatureinclude the above-noted SHA1 secure hashing algorithm, or other securehashing algorithms known to those skilled in the art, including SHA2,SHA256 and many others. The content-based signature is utilized todetermine the location of the corresponding user data page within theuser data area of the storage devices 406.

Each of the metadata pages 420 in the present embodiment is assumed tohave a signature that is not content-based. For example, the metadatapage signatures may be generated using hash functions or other signaturegeneration algorithms that do not utilize content of the metadata pagesas input to the signature generation algorithm. Also, each of themetadata pages is assumed to characterize a different set of the userdata pages.

A given set of metadata pages representing a portion of the metadatapages 420 in an illustrative embodiment comprises metadata pages denotedMetadata Page 1, Metadata Page 2, . . . Metadata Page m, havingrespective signatures denoted Signature 1, Signature 2, . . . Signaturem. Each such metadata page characterizes a different set of n user datapages. For example, the characterizing information in each metadata pagecan include the LUN identifiers, offsets and content-based signaturesfor each of the n user data pages that are characterized by thatmetadata page. It is to be appreciated, however, that the user data andmetadata page configurations described above are examples only, andnumerous alternative user data and metadata page configurations can beused in other embodiments.

Ownership of a user data logical address space within the contentaddressable storage system 405 is illustratively distributed among thecontrol modules 408C.

The flow control functionality provided by modules 412 and 414 in thisembodiment is assumed to be distributed across multiple distributedprocessing modules, including at least a subset of the processingmodules 408C, 408D, 408R and 408M of the distributed storage controller408.

For example, the management module 408M of the storage controller 408may include a replication control logic instance that engagescorresponding replication control logic instances in all of the controlmodules 408C and routing modules 408R in order to implement asynchronous replication process. In some embodiments, the contentaddressable storage system 405 comprises an XtremIO storage arraysuitably modified to incorporate flow control functionality as disclosedherein.

In arrangements of this type, the control modules 408C, data modules408D and routing modules 408R of the distributed storage controller 408illustratively comprise respective C-modules, D-modules and R-modules ofthe XtremIO storage array. The one or more management modules 408M ofthe distributed storage controller 408 in such arrangementsillustratively comprise a system-wide management module (“SYM module”)of the XtremIO storage array, although other types and arrangements ofsystem-wide management modules can be used in other embodiments.Accordingly, flow control functionality in some embodiments isimplemented under the control of at least one system-wide managementmodule of the distributed storage controller 408, utilizing theC-modules, D-modules and R-modules of the XtremIO storage array.

In the above-described XtremIO storage array example, each user datapage has a fixed size such as 8 KB and its content-based signature is a20-byte signature generated using the SHA1 secure hashing algorithm.Also, each page has a LUN identifier and an offset, and so ischaracterized by <lun_id, offset, signature>.

The content-based signature in the present example comprises acontent-based digest of the corresponding data page. Such acontent-based digest is more particularly referred to as a “hash digest”of the corresponding data page, as the content-based signature isillustratively generated by applying a hash function such as the SHA1secure hashing algorithm to the content of that data page. The full hashdigest of a given data page is given by the above-noted 20-bytesignature. The hash digest may be represented by a corresponding “hashhandle,” which in some cases may comprise a particular portion of thehash digest. The hash handle illustratively maps on a one-to-one basisto the corresponding full hash digest within a designated clusterboundary or other specified storage resource boundary of a given storagesystem. In arrangements of this type, the hash handle provides alightweight mechanism for uniquely identifying the corresponding fullhash digest and its associated data page within the specified storageresource boundary. The hash digest and hash handle are both consideredexamples of “content-based signatures” as that term is broadly usedherein.

Examples of techniques for generating and processing hash handles forrespective hash digests of respective data pages are disclosed in U.S.Pat. No. 9,208,162, entitled “Generating a Short Hash Handle,” and U.S.Pat. No. 9,286,003, entitled “Method and Apparatus for Creating a ShortHash Handle Highly Correlated with a Globally-Unique Hash Signature,”both of which are incorporated by reference herein.

As mentioned previously, storage controller components in an XtremIOstorage array illustratively include C-module, D-module and R-modulecomponents. For example, separate instances of such components can beassociated with each of a plurality of storage nodes in a clusteredstorage system implementation.

The distributed storage controller in this example is configured togroup consecutive pages into page groups, to arrange the page groupsinto slices, and to assign the slices to different ones of theC-modules. For example, if there are 1024 slices distributed evenlyacross the C-modules, and there are a total of 16 C-modules in a givenimplementation, each of the C-modules “owns” 1024/16=64 slices. In sucharrangements, different ones of the slices are assigned to differentones of the control modules 408C such that control of the slices withinthe storage controller 408 of the storage system 405 is substantiallyevenly distributed over the control modules 408C of the storagecontroller 408.

The D-module allows a user to locate a given user data page based on itssignature. Each metadata page also has a size of 8 KB and includesmultiple instances of the <lun_id, offset, signature> for respectiveones of a plurality of the user data pages. Such metadata pages areillustratively generated by the C-module but are accessed using theD-module based on a metadata page signature.

The metadata page signature in this embodiment is a 20-byte signaturebut is not based on the content of the metadata page. Instead, themetadata page signature is generated based on an 8-byte metadata pageidentifier that is a function of the LUN identifier and offsetinformation of that metadata page.

If a user wants to read a user data page having a particular LUNidentifier and offset, the corresponding metadata page identifier isfirst determined, then the metadata page signature is computed for theidentified metadata page, and then the metadata page is read using thecomputed signature. In this embodiment, the metadata page signature ismore particularly computed using a signature generation algorithm thatgenerates the signature to include a hash of the 8-byte metadata pageidentifier, one or more ASCII codes for particular predeterminedcharacters, as well as possible additional fields. The last bit of themetadata page signature may always be set to a particular logic value soas to distinguish it from the user data page signature in which the lastbit may always be set to the opposite logic value.

The metadata page signature is used to retrieve the metadata page viathe D-module. This metadata page will include the <lun_id, offset,signature> for the user data page if the user page exists. The signatureof the user data page is then used to retrieve that user data page, alsovia the D-module.

Write requests processed in the content addressable storage system 405each illustratively comprise one or more IO operations directing that atleast one data item of the storage system 405 be written to in aparticular manner. A given write request is illustratively received inthe storage system 405 from a host device over a network. In someembodiments, a write request is received in the distributed storagecontroller 408 of the storage system 405 and directed from oneprocessing module to another processing module of the distributedstorage controller 408. For example, a received write request may bedirected from a routing module 408R of the distributed storagecontroller 408 to a particular control module 408C of the distributedstorage controller 408. Other arrangements for receiving and processingwrite requests from one or more host devices can be used.

The term “write request” as used herein is intended to be broadlyconstrued, so as to encompass one or more IO operations directing thatat least one data item of a storage system be written to in a particularmanner. A given write request is illustratively received in a storagesystem from a host device.

In the XtremIO context, the C-modules, D-modules and R-modules of thestorage nodes 415 communicate with one another over a high-speedinternal network such as an InfiniBand network. The C-modules, D-modulesand R-modules coordinate with one another to accomplish various IOprocessing tasks.

The write requests from the host devices identify particular data pagesto be written in the storage system 405 by their corresponding logicaladdresses each comprising a LUN ID and an offset.

As noted above, a given one of the content-based signaturesillustratively comprises a hash digest of the corresponding data page,with the hash digest being generated by applying a hash function to thecontent of that data page. The hash digest may be uniquely representedwithin a given storage resource boundary by a corresponding hash handle.

The content addressable storage system 405 utilizes a two-level mappingprocess to map logical block addresses to physical block addresses. Thefirst level of mapping uses an address-to-hash (“A2H”) table and thesecond level of mapping uses a hash metadata (“HMD”) table, with the A2Hand HMD tables corresponding to respective logical and physical layersof the content-based signature mapping within the content addressablestorage system 405. The HMD table or a given portion thereof in someembodiments disclosed herein is more particularly referred to as ahash-to-data (“H2D”) table.

The first level of mapping using the A2H table associates logicaladdresses of respective data pages with respective content-basedsignatures of those data pages. This is also referred to as logicallayer mapping. The second level of mapping using the HMD tableassociates respective ones of the content-based signatures withrespective physical storage locations in one or more of the storagedevices 106. This is also referred to as physical layer mapping.

Examples of these and other metadata structures utilized in illustrativeembodiments were described above in conjunction with FIG. 2. Theseparticular examples include respective A2H, H2D, HMD and PLB tables. Insome embodiments, the A2H and H2D tables are utilized primarily by thecontrol modules 408C, while the HMD and PLB tables are utilizedprimarily by the data modules 408D.

For a given write request, hash metadata comprising at least a subset ofthe above-noted tables is updated in conjunction with the processing ofthat write request. The A2H, H2D, HMD and PLB tables described above areexamples of what are more generally referred to herein as “mappingtables” of respective distinct types. Other types and arrangements ofmapping tables or other content-based signature mapping information maybe used in other embodiments. Such mapping tables are still moregenerally referred to herein as “metadata structures” of the contentaddressable storage system 405. It should be noted that additional oralternative metadata structures can be used in other embodiments.References herein to particular tables of particular types, such as A2H,H2D, HMD and PLB tables, and their respective configurations, should beconsidered non-limiting and are presented by way of illustrative exampleonly. Such metadata structures can be implemented in numerousalternative configurations with different arrangements of fields andentries in other embodiments.

The logical block addresses or LBAs of a logical layer of the storagesystem 405 correspond to respective physical blocks of a physical layerof the storage system 405. The user data pages of the logical layer areorganized by LBA and have reference via respective content-basedsignatures to particular physical blocks of the physical layer.

Each of the physical blocks has an associated reference count that ismaintained within the storage system 405. The reference count for agiven physical block indicates the number of logical blocks that pointto that same physical block.

In releasing logical address space in the storage system, adereferencing operation is generally executed for each of the LBAs beingreleased. More particularly, the reference count of the correspondingphysical block is decremented. A reference count of zero indicates thatthere are no longer any logical blocks that reference the correspondingphysical block, and so that physical block can be released.

It should also be understood that the particular arrangement of storagecontroller processing modules 408C, 408D, 408R and 408M as shown in theFIG. 4 embodiment is presented by way of example only. Numerousalternative arrangements of processing modules of a distributed storagecontroller may be used to implement flow control functionality in aclustered storage system in other embodiments.

Additional examples of content addressable storage functionalityimplemented in some embodiments by control modules 408C, data modules408D, routing modules 408R and management module(s) 408M of distributedstorage controller 408 can be found in U.S. Pat. No. 9,104,326, entitled“Scalable Block Data Storage Using Content Addressing,” which isincorporated by reference herein. Alternative arrangements of these andother storage node processing modules of a distributed storagecontroller in a content addressable storage system can be used in otherembodiments.

In some embodiments, the local and remote storage systems areillustratively implemented as respective content addressable storagesystems, but in other embodiments one or more of the storage systems caninstead be a traditional storage array, which does not support any typeof content addressable storage functionality, with any missingfunctionality being provided by a host device. Accordingly,functionality for flow control in synchronous replication as disclosedherein can be implemented in a storage system, in a host device, orpartially in a storage system and partially in a host device.

It is to be appreciated that the particular advantages described aboveand elsewhere herein are associated with particular illustrativeembodiments and need not be present in other embodiments. Also, theparticular types of information processing system features andfunctionality as illustrated in the drawings and described above areexemplary only, and numerous other arrangements may be used in otherembodiments.

Illustrative embodiments of processing platforms utilized to implementhost devices and storage systems with flow control functionality willnow be described in greater detail with reference to FIGS. 5 and 6.Although described in the context of system 100, these platforms mayalso be used to implement at least portions of other informationprocessing systems in other embodiments.

FIG. 5 shows an example processing platform comprising cloudinfrastructure 500. The cloud infrastructure 500 comprises a combinationof physical and virtual processing resources that may be utilized toimplement at least a portion of the information processing system 100.The cloud infrastructure 500 comprises multiple virtual machines (VMs)and/or container sets 502-1, 502-2, . . . 502-L implemented usingvirtualization infrastructure 504. The virtualization infrastructure 504runs on physical infrastructure 505, and illustratively comprises one ormore hypervisors and/or operating system level virtualizationinfrastructure. The operating system level virtualization infrastructureillustratively comprises kernel control groups of a Linux operatingsystem or other type of operating system.

The cloud infrastructure 500 further comprises sets of applications510-1, 510-2, . . . 510L running on respective ones of the VMs/containersets 502-1, 502-2, . . . 502-L under the control of the virtualizationinfrastructure 504. The VMs/container sets 502 may comprise respectiveVMs, respective sets of one or more containers, or respective sets ofone or more containers running in VMs.

In some implementations of the FIG. 5 embodiment, the VMs/container sets502 comprise respective VMs implemented using virtualizationinfrastructure 504 that comprises at least one hypervisor. Suchimplementations can provide flow control functionality of the typedescribed above for one or more processes running on a given one of theVMs. For example, each of the VMs can implement replication controllogic and/or flow controllers for providing flow control functionalityin the system 100.

An example of a hypervisor platform that may be used to implement ahypervisor within the virtualization infrastructure 504 is the VMware®vSphere® which may have an associated virtual infrastructure managementsystem such as the VMware® vCenter™. The underlying physical machinesmay comprise one or more distributed processing platforms that includeone or more storage systems. In other implementations of the FIG. 5embodiment, the VMs/container sets 502 comprise respective containersimplemented using virtualization infrastructure 504 that providesoperating system level virtualization functionality, such as support forDocker containers running on bare metal hosts, or Docker containersrunning on VMs. The containers are illustratively implemented usingrespective kernel control groups of the operating system. Suchimplementations can also provide flow control functionality of the typedescribed above. For example, a container host device supportingmultiple containers of one or more container sets can implement one ormore instances of replication control logic and/or flow controllers forproviding flow control functionality in the system 100.

As is apparent from the above, one or more of the processing modules orother components of system 100 may each run on a computer, server,storage device or other processing platform element. A given suchelement may be viewed as an example of what is more generally referredto herein as a “processing device.” The cloud infrastructure 500 shownin FIG. 5 may represent at least a portion of one processing platform.Another example of such a processing platform is processing platform 600shown in FIG. 6.

The processing platform 600 in this embodiment comprises a portion ofsystem 100 and includes a plurality of processing devices, denoted602-1, 602-2, 602-3, . . . 602-K, which communicate with one anotherover a network 604.

The network 604 may comprise any type of network, including by way ofexample a global computer network such as the Internet, a WAN, a LAN, asatellite network, a telephone or cable network, a cellular network, awireless network such as a WiFi or WiMAX network, or various portions orcombinations of these and other types of networks.

The processing device 602-1 in the processing platform 600 comprises aprocessor 610 coupled to a memory 612. The processor 610 may comprise amicroprocessor, a microcontroller, an application-specific integratedcircuit (ASIC), a field-programmable gate array (FPGA), graphicsprocessing unit (GPU) or other type of processing circuitry, as well asportions or combinations of such circuitry elements.

The memory 612 may comprise random access memory (RAM), read-only memory(ROM), flash memory or other types of memory, in any combination. Thememory 612 and other memories disclosed herein should be viewed asillustrative examples of what are more generally referred to as“processor-readable storage media” storing executable program code ofone or more software programs.

Articles of manufacture comprising such processor-readable storage mediaare considered illustrative embodiments. A given such article ofmanufacture may comprise, for example, a storage array, a storage diskor an integrated circuit containing RAM, ROM, flash memory or otherelectronic memory, or any of a wide variety of other types of computerprogram products. The term “article of manufacture” as used hereinshould be understood to exclude transitory, propagating signals.Numerous other types of computer program products comprisingprocessor-readable storage media can be used.

Also included in the processing device 602-1 is network interfacecircuitry 614, which is used to interface the processing device with thenetwork 604 and other system components and may comprise conventionaltransceivers.

The other processing devices 602 of the processing platform 600 areassumed to be configured in a manner similar to that shown forprocessing device 602-1 in the figure.

Again, the particular processing platform 600 shown in the figure ispresented by way of example only, and system 100 may include additionalor alternative processing platforms, as well as numerous distinctprocessing platforms in any combination, with each such platformcomprising one or more computers, servers, storage devices or otherprocessing devices.

For example, other processing platforms used to implement illustrativeembodiments can comprise converged infrastructure such as VxRail™,VxRack™, VxRack™ FLEX, VxBlock™, or Vblock® converged infrastructurefrom VCE, the Virtual Computing Environment Company, now the ConvergedPlatform and Solutions Division of Dell EMC.

It should therefore be understood that in other embodiments differentarrangements of additional or alternative elements may be used. At leasta subset of these elements may be collectively implemented on a commonprocessing platform, or each such element may be implemented on aseparate processing platform.

As indicated previously, components of an information processing systemas disclosed herein can be implemented at least in part in the form ofone or more software programs stored in memory and executed by aprocessor of a processing device. For example, at least portions of theflow control functionality of one or more components of a storage systemas disclosed herein are illustratively implemented in the form ofsoftware running on one or more processing devices.

It should again be emphasized that the above-described embodiments arepresented for purposes of illustration only. Many variations and otheralternative embodiments may be used. For example, the disclosedtechniques are applicable to a wide variety of other types ofinformation processing systems, host devices, storage systems, storagenodes, storage devices, storage controllers, synchronous replicationprocesses, flow controllers and associated control logic and metadatastructures. Also, the particular configurations of system and deviceelements and associated processing operations illustratively shown inthe drawings can be varied in other embodiments. Moreover, the variousassumptions made above in the course of describing the illustrativeembodiments should also be viewed as exemplary rather than asrequirements or limitations of the disclosure. Numerous otheralternative embodiments within the scope of the appended claims will bereadily apparent to those skilled in the art.

What is claimed is:
 1. A method for performing flow control for asynchronous replication session between a local storage and a remotestorage in a storage system, the method comprising: tracking an amountof time an input/output (IO) request is processed at the remote storageincluding an amount of time the IO request is in transmit to and fromthe remote storage system, the amount of time indicating a remotelatency value; tracking an amount of time the IO request is processed atthe local storage; calculating a difference between the remote latencyvalue and the amount of time the IO request is processed at the localstorage, the difference indicating a local latency value; and modifyingan amount of IO requests admitted at the storage system as a function ofthe local latency value.
 2. The method of claim 1, wherein tracking theamount of time the IO request is processed at the remote storageincluding the amount of time the IO request is in transit includes:recording, by the local storage, a first timestamp upon receiving the IOat the local storage; recording, by the local storage, a secondtimestamp upon transmitting the IO request to the remote storage;recording, by the local storage, a third timestamp upon receiving anacknowledgment from the remote storage that the IO request has completedat the remote storage; and calculating a difference between the thirdtimestamp and the second timestamp, the difference indicating the remotelatency value.
 3. The method of claim 2, wherein tracking an amount oftime the IO request is processed at the local storage includes:recording, at the local storage, a fourth timestamp upon completion ofprocessing of the IO at the local storage; and calculating a differencebetween the fourth timestamp and the first timestamp.
 4. The method ofclaim 3, wherein calculating a difference between the remote latencyvalue and the amount of time the IO request is processed at the localstorage comprises subtracting the remote latency value from thedifference between the fourth timestamp and the first timestamp.
 5. Themethod of claim 1, wherein modifying the amount of IO requests admittedto the storage system as a function of the local latency value comprisesincreasing an amount of the IO requests admitted to the storage systemupon determining the local latency value is below a threshold value. 6.The method of claim 1, wherein modifying the amount of IO requestsadmitted to the storage system as a function of the local latency valuecomprises decreasing an amount of the IO requests admitted to thestorage system upon determining the local latency value exceeds athreshold value.
 7. The method of claim 1, wherein modifying the amountof IO requests admitted to the storage system as a function of the locallatency value comprises maintaining an amount of the IO requestsadmitted to the storage system upon determining the local latency valuemeets a threshold value.
 8. The method of claim 1, wherein the storagesystem includes a content addressable storage system.
 9. A system forperforming flow control for a synchronous replication session between alocal storage and a remote storage of a storage system, the systemcomprising: a memory comprising computer-executable instructions; and aprocessor operable by a storage system, the processor executing thecomputer-executable instructions, the computer-executable instructionswhen executed by the processor cause the processor to perform operationscomprising: tracking an amount of time an input/output (IO) request isprocessed at the remote storage including an amount of time the IOrequest is in transmit to and from the remote storage system, the amountof time indicating a remote latency value; tracking an amount of timethe IO request is processed at the local storage; calculating adifference between the remote latency value and the amount of time theIO request is processed at the local storage, the difference indicatinga local latency value; and modifying an amount of IO requests admittedat the storage system as a function of the local latency value.
 10. Thesystem of claim 9, wherein tracking the amount of time the IO request isprocessed at the remote storage including the amount of time the IOrequest is in transit includes: recording, by the local storage, a firsttimestamp upon receiving the IO at the local storage; recording, by thelocal storage, a second timestamp upon transmitting the IO request tothe remote storage; recording, by the local storage, a third timestampupon receiving an acknowledgment from the remote storage that the IOrequest has completed at the remote storage; and calculating adifference between the third timestamp and the second timestamp, thedifference indicating the remote latency value.
 11. The system of claim10, wherein tracking an amount of time the IO request is processed atthe local storage includes: recording, at the local storage, a fourthtimestamp upon completion of processing of the IO at the local storage;and calculating a difference between the fourth timestamp and the firsttimestamp.
 12. The system of claim 11, wherein calculating a differencebetween the remote latency value and the amount of time the IO requestis processed at the local storage comprises subtracting the remotelatency value from the difference between the fourth timestamp and thefirst timestamp.
 13. The system of claim 9, wherein modifying the amountof IO requests admitted to the storage system as a function of the locallatency value comprises: increasing an amount of the IO requestsadmitted to the storage system upon determining the local latency valueis below a threshold value; decreasing an amount of the IO requestsadmitted to the storage system upon determining the local latency valueexceeds a threshold value; and maintaining an amount of the IO requestsadmitted to the storage system upon determining the local latency valuemeets a threshold value.
 14. The system of claim 9, wherein the storagesystem includes a content addressable storage system.
 15. A computerprogram product performing flow control for a synchronous replicationsession between a local storage and a remote storage of a storagesystem, the computer program product embodied on a non-transitorycomputer readable medium, the computer program product includinginstructions that, when executed by a computer, causes the computer toperform operations comprising: tracking an amount of time aninput/output (IO) request is processed at the remote storage includingan amount of time the IO request is in transmit to and from the remotestorage system, the amount of time indicating a remote latency value;tracking an amount of time the IO request is processed at the localstorage; calculating a difference between the remote latency value andthe amount of time the IO request is processed at the local storage, thedifference indicating a local latency value; and modifying an amount ofIO requests admitted at the storage system as a function of the locallatency value.
 16. The computer program product of claim 15, whereintracking the amount of time the IO request is processed at the remotestorage including the amount of time the IO request is in transitincludes: recording, by the local storage, a first timestamp uponreceiving the IO at the local storage; recording, by the local storage,a second timestamp upon transmitting the IO request to the remotestorage; recording, by the local storage, a third timestamp uponreceiving an acknowledgment from the remote storage that the IO requesthas completed at the remote storage; and calculating a differencebetween the third timestamp and the second timestamp, the differenceindicating the remote latency value.
 17. The computer program product ofclaim 16, wherein tracking an amount of time the IO request is processedat the local storage includes: recording, at the local storage, a fourthtimestamp upon completion of processing of the IO at the local storage;and calculating a difference between the fourth timestamp and the firsttimestamp.
 18. The computer program product of claim 17, whereincalculating a difference between the remote latency value and the amountof time the IO request is processed at the local storage comprisessubtracting the remote latency value from the difference between thefourth timestamp and the first timestamp.
 19. The computer programproduct of claim 15, wherein modifying the amount of IO requestsadmitted to the storage system as a function of the local latency valuecomprises: increasing an amount of the IO requests admitted to thestorage system upon determining the local latency value is below athreshold value; decreasing an amount of the IO requests admitted to thestorage system upon determining the local latency value exceeds athreshold value; and maintaining an amount of the IO requests admittedto the storage system upon determining the local latency value meets athreshold value.
 20. The computer program product of claim 15, whereinthe storage system includes a content addressable storage system.